1. A DATA PLANNING FRAMEWORK FOR DISASTER RESPONSE KEN KEISER MANIL MASKEY* UNIVERSITY OF ALABAMA IN HUNTSVILLE ESIP Summer Meeting Session on: Data System Architecture in Support of Disaster Response and Awareness

2. “...the aftermath of a major disaster is no time to be exchanging business cards.” Planning and preparedness can greatly improve the quality and latency of responses to events. Good planning leads to organized and effective emergency response. Emergency preparedness means taking action to be ready for emergencies before they happen. The objective of emergency preparedness is to simplify decision-making during emergencies. Emergency Preparedness and Response, Some Issues and Challenges Associated with Major Emergency Incidents, Statement of William O. Jenkins, Jr., Director Homeland Security and Justice Issues, United States Government Accountability Office Report GAO-06-467T, 2006.

3. Goals of the NASA Applied Science Feasibility Project Use Event-Driven Data Delivery (ED3) to prepare for data needs prior to disaster (and other) events. Demonstrate the feasibility of an ED3 framework to support improved data preparedness for Decision Support Systems, applications, and users. Provide reusable framework components that can support different events, disciplines, and data and processing needs. Acknowledgements: This research is supported by the National Aeronautic and Space Administration grant NNX12AP73G. The project team includes PI Sara Graves and Co-Is Udaysankar Nair and Ken Keiser, all at the University of Alabama in Huntsville. Frank Lindsay is the NASA Applied Science program manager for this project.

4. Data Preparedness Plans & Services Service Layer Plan Database Events Data Workflows Decision Systems and Users Preparedness Plan: For this event type Meeting this criteria, Do this processing

5. Decision Support Systems & Users Decision Systems & Users Custom Applications Existing decision support systems Service Layer Plans Preparedness Plan: For this event type Meeting this criteria, Do this processing Any authorized system may generate and submit plans

6. Events Trigger Plans Service Layer Plans Event Generators Common Alerting Protocol (CAP) Event Listener Trigger Matching Preparedness Plans Event Generators If the plan is for this type of event, and if specifies this criteria, then execute plan

7. Workflow Manager Process Plan Workflows Service Layer Plans Workflow Managers Data Access Sensor Tasking Sensor Tasking Product Generation Process and Package Request Open Jobs of Supported Processing Receive Jobs To Be Processed Data Repositories ISERV Workflow manager components can be specialized for different types of data and processing. Multiple workflow managers can service a single plan. Virtual Products Pre-negotiate access and agreements Near – Future?

8. Workflow Managers System/User Notifications Service Layer Plans Event Listener Workflow Managers Event Detection Workflow Processing Plan Generation Notifications by email, call-back functions, and others as necessary.

9. ED3 Use Case for NGCHC Matching Plan is selected by the proper Workflow Manager for execution Notification of plan execution and results are sent to NGCHC viz/situational awareness tool Requested data is retrieved and packaged storm notification issued and picked up by Event Listener Storm advisories determine potential for storm in area of interest DSS Creates Preparedness Plan based on occurrence of tropical storm events Event / Prediction Data sources: Archives Regional Observations Modelers Analysts Data Types: Model Outputs CSV KML W*S Working with RENCI for ADCIRC outputs Aggregation of Models, Observations, and Analysis for the events with subscribed data

10. Example Flood Use Case Matching Plan is selected by the proper Workflow Manager for execution Additional workflows executed as necessary based on latest models or actual event occurrence Notification of plan execution and results are sent to DSS Requested data is retrieved and higher resolution modeling run initiated Flood Potential notification issued and picked up by Event Listener Regional flood model determines potential for flood in area of interest DSS Creates Preparedness Plan based on occurrence of Flood Potential Topography Rainfall Soil Moisture Model Event / Prediction Data Inputs

11. Alabama Past and Potential Disaster Threats and Example Data Needs Tornado - Aerial photos as well as Landsat, SPOT, and other International Charter satellite data (April 2011 massive example) Environmental - Satellite and aerial data (color and IR) (DeepwaterHorizon as an example) Hurricane – Aerial imagery, LANDSAT, LIDAR, MODIS for during/after event analysis Winter/Ice Storms - Soil-based data such as USDA/NRCS soils vector and tabular data Earthquake – (pre and post-event) high-res satellite imagery, aerial imagery, RADAR and LiDAR data (to generate interferograms) Landslide - Aerial imagery, high-res elevation data, RADAR and LIDAR, for change detection and slope analysis Sinkholes - LiDAR data and aerial imagery (4-band) Flood – Aerial and LIDAR, elevation and floodplain data Drought – LANDSAT, aerial imagery and spectral data for vegetation classification and analysis Wildfire – Thermal data during fires, and visual land data for pre/post comparisons and analysis Tsunami - Aerial imagery, LANDSAT, LIDAR, MODIS for analysis during and after the event Radiological – Thermal and reflected data for both aerial and satellite coverage

12. Alabama State Emergency Support Functions and Responsible Agencies/Departments Transportation: AL DOT and AL EMA Communications: AL EMA Public Works and Engineering: AL DOT and public Utilities Firefighting: AL Forestry Commission Emergency Management: AL EMA Mass Care: Emergency Assistance and Housing and Human Services Logistics Management and Resource Support: AL EMA Public Health and Medical Services: Dept of Public Health Search and Rescue: AL EMA Oil and Hazardous Materials Response: ADEM Agriculture and Natural Resources: AL Dept of Agriculture and Industries, AL Dept of Conservation and Natural Resources Energy: ADECA (utilities) Public Safety and Security: AL Dept of Public Safety Long-Term Community Recovery: Govenor’sOffice External Affairs: AL EMA

13. Ongoing and Planned Use Cases Hurricane/Coastal Impacts – UAH ITSC with Northern Gulf Coastal Hazards Collaboratory (NG CHC) participants. Land Slide Potential – UAH Atmospheric Science and Geological Survey of Alabama, NH CHC SERVIR – Integrating event notifications with SERVIR data processing workflows to provide more rapid response to some events and potential tasking of the ISERV instrument. Flood Prediction – UAH Atmospheric Science, SERVIR (international), and GSA (S.E U.S. regional) Super Fog Transportation Conditions – UAH Atmospheric Science, ITSC and Alabama Forestry Commission Intelligence Community – ITSC and IC partners

14. Use Case: Super Fog Transportation Conditions Interface with previous Applied Science project that models the air quality and visibility impacts of controlled burns within the state. Collaboration with the Alabama Forestry Commission Potential event generator for transportation warnings and impacts on other smoke sensitive features.

15. Alabama Forestry Commission Permit DB Permit DB University of Alabama In Huntsville NASA Data Atmospheric Conditions Dispersion and AQ Models Output Current Permits Current Permits GIS Db GIS Db GeoServer Web GIS Environment Virtual Alabama High-Level Architecture Current AQ conditions AQ and Visibility Warnings/Notifications

16. Challenges Generically handling event notices from multiple sources Generalizing event criteria across event types Supporting and handling all data workflows Communicating processing notices in various forms to support variety of DSS approaches

17. Lessons Learned Keep architecture loosely coupled to external components Identify interested stakeholders early and work closely with them to identify requirements Reference Implementations are extremely useful to work out integration problems

18. Project Participants Project Team Sara Graves (PI) – UAH Information Technology and Systems Center Udaysankar Nair (Co-I) UAH Atmospheric Science Dept. Current Collaborators Global Hydrology Resource Center (GHRC) – NASA/MSFC Northern Gulf Coastal Hazards Collaboratory (LA, MS, AL) Geological Survey of Alabama SERVIR/ISERV Reference Implementation Http://ed3test.itsc.uah.edu/ Acknowledgements: This research is supported by the National Aeronautic and Space Administration grant NNX12AP73G. Frank Lindsay is the NASA Applied Science program manager for this project.